E. S. Euskirchen

2023

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Evaluating photosynthetic activity across Arctic-Boreal land cover types using solar-induced fluorescence
Rui Cheng, Troy S. Magney, Erica L Orcutt, Zoe Pierrat, Philipp Köhler, D. R. Bowling, M. Syndonia Bret‐Harte, E. S. Euskirchen, Martin Jung, Hideki Kobayashi, Adrian V. Rocha, Oliver Sonnentag, J. Stutz, Sophia Walther, Donatella Zona, Christian Frankenberg, Rui Cheng, Troy S. Magney, Erica L Orcutt, Zoe Pierrat, Philipp Köhler, D. R. Bowling, M. Syndonia Bret‐Harte, E. S. Euskirchen, Martin Jung, Hideki Kobayashi, Adrian V. Rocha, Oliver Sonnentag, J. Stutz, Sophia Walther, Donatella Zona, Christian Frankenberg
Environmental Research Letters, Volume 17, Issue 11

Abstract Photosynthesis of terrestrial ecosystems in the Arctic-Boreal region is a critical part of the global carbon cycle. Solar-induced chlorophyll Fluorescence (SIF), a promising proxy for photosynthesis with physiological insight, has been used to track gross primary production (GPP) at regional scales. Recent studies have constructed empirical relationships between SIF and eddy covariance-derived GPP as a first step to predicting global GPP. However, high latitudes pose two specific challenges: (a) Unique plant species and land cover types in the Arctic–Boreal region are not included in the generalized SIF-GPP relationship from lower latitudes, and (b) the complex terrain and sub-pixel land cover further complicate the interpretation of the SIF-GPP relationship. In this study, we focused on the Arctic-Boreal vulnerability experiment (ABoVE) domain and evaluated the empirical relationships between SIF for high latitudes from the TROPOspheric Monitoring Instrument (TROPOMI) and a state-of-the-art machine learning GPP product (FluxCom). For the first time, we report the regression slope, linear correlation coefficient, and the goodness of the fit of SIF-GPP relationships for Arctic-Boreal land cover types with extensive spatial coverage. We found several potential issues specific to the Arctic-Boreal region that should be considered: (a) unrealistically high FluxCom GPP due to the presence of snow and water at the subpixel scale; (b) changing biomass distribution and SIF-GPP relationship along elevational gradients, and (c) limited perspective and misrepresentation of heterogeneous land cover across spatial resolutions. Taken together, our results will help improve the estimation of GPP using SIF in terrestrial biosphere models and cope with model-data uncertainties in the Arctic-Boreal region.

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Modeled production, oxidation, and transport processes of wetland methane emissions in temperate, boreal, and Arctic regions
Masahito Ueyama, Sara Knox, Kyle Delwiche, Sheel Bansal, W. J. Riley, Dennis Baldocchi, Takashi Hirano, Gavin McNicol, K. V. Schäfer, L. Windham‐Myers, Benjamin Poulter, Robert B. Jackson, Kuang‐Yu Chang, Jiquen Chen, Housen Chu, Ankur R. Desai, Sébastien Gogo, Hiroki Iwata, Minseok Kang, Ivan Mammarella, Matthias Peichl, Oliver Sonnentag, Eeva‐Stiina Tuittila, Youngryel Ryu, E. S. Euskirchen, Mathias Göckede, Adrien Jacotot, Mats B. Nilsson, Torsten Sachs, Masahito Ueyama, Sara Knox, Kyle Delwiche, Sheel Bansal, W. J. Riley, Dennis Baldocchi, Takashi Hirano, Gavin McNicol, K. V. Schäfer, L. Windham‐Myers, Benjamin Poulter, Robert B. Jackson, Kuang‐Yu Chang, Jiquen Chen, Housen Chu, Ankur R. Desai, Sébastien Gogo, Hiroki Iwata, Minseok Kang, Ivan Mammarella, Matthias Peichl, Oliver Sonnentag, Eeva‐Stiina Tuittila, Youngryel Ryu, E. S. Euskirchen, Mathias Göckede, Adrien Jacotot, Mats B. Nilsson, Torsten Sachs
Global Change Biology, Volume 29, Issue 8

Wetlands are the largest natural source of methane (CH4 ) to the atmosphere. The eddy covariance method provides robust measurements of net ecosystem exchange of CH4 , but interpreting its spatiotemporal variations is challenging due to the co-occurrence of CH4 production, oxidation, and transport dynamics. Here, we estimate these three processes using a data-model fusion approach across 25 wetlands in temperate, boreal, and Arctic regions. Our data-constrained model-iPEACE-reasonably reproduced CH4 emissions at 19 of the 25 sites with normalized root mean square error of 0.59, correlation coefficient of 0.82, and normalized standard deviation of 0.87. Among the three processes, CH4 production appeared to be the most important process, followed by oxidation in explaining inter-site variations in CH4 emissions. Based on a sensitivity analysis, CH4 emissions were generally more sensitive to decreased water table than to increased gross primary productivity or soil temperature. For periods with leaf area index (LAI) of ≥20% of its annual peak, plant-mediated transport appeared to be the major pathway for CH4 transport. Contributions from ebullition and diffusion were relatively high during low LAI (<20%) periods. The lag time between CH4 production and CH4 emissions tended to be short in fen sites (3 ± 2 days) and long in bog sites (13 ± 10 days). Based on a principal component analysis, we found that parameters for CH4 production, plant-mediated transport, and diffusion through water explained 77% of the variance in the parameters across the 19 sites, highlighting the importance of these parameters for predicting wetland CH4 emissions across biomes. These processes and associated parameters for CH4 emissions among and within the wetlands provide useful insights for interpreting observed net CH4 fluxes, estimating sensitivities to biophysical variables, and modeling global CH4 fluxes.

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Carbon uptake in Eurasian boreal forests dominates the high‐latitude net ecosystem carbon budget
Jennifer D. Watts, Mary Farina, John S. Kimball, Luke D. Schiferl, Zhihua Liu, Kyle A. Arndt, Donatella Zona, Ashley P. Ballantyne, E. S. Euskirchen, Frans‐Jan W. Parmentier, Manuel Helbig, Oliver Sonnentag, Torbern Tagesson, Janne Rinne, Hiroki Ikawa, Masahito Ueyama, Hideki Kobayashi, Torsten Sachs, Daniel F. Nadeau, John Kochendorfer, M. Jackowicz-Korczyński, Anna Virkkala, Mika Aurela, R. Commane, Brendan Byrne, Leah Birch, Matthew S. Johnson, Nima Madani, Brendan M. Rogers, Jinyang Du, Arthur Endsley, K. E. Savage, Benjamin Poulter, Zhen Zhang, L. M. Bruhwiler, Charles E. Miller, S. J. Goetz, Walter C. Oechel, Jennifer D. Watts, Mary Farina, John S. Kimball, Luke D. Schiferl, Zhihua Liu, Kyle A. Arndt, Donatella Zona, Ashley P. Ballantyne, E. S. Euskirchen, Frans‐Jan W. Parmentier, Manuel Helbig, Oliver Sonnentag, Torbern Tagesson, Janne Rinne, Hiroki Ikawa, Masahito Ueyama, Hideki Kobayashi, Torsten Sachs, Daniel F. Nadeau, John Kochendorfer, M. Jackowicz-Korczyński, Anna Virkkala, Mika Aurela, R. Commane, Brendan Byrne, Leah Birch, Matthew S. Johnson, Nima Madani, Brendan M. Rogers, Jinyang Du, Arthur Endsley, K. E. Savage, Benjamin Poulter, Zhen Zhang, L. M. Bruhwiler, Charles E. Miller, S. J. Goetz, Walter C. Oechel
Global Change Biology, Volume 29, Issue 7

Arctic-boreal landscapes are experiencing profound warming, along with changes in ecosystem moisture status and disturbance from fire. This region is of global importance in terms of carbon feedbacks to climate, yet the sign (sink or source) and magnitude of the Arctic-boreal carbon budget within recent years remains highly uncertain. Here, we provide new estimates of recent (2003-2015) vegetation gross primary productivity (GPP), ecosystem respiration (Reco ), net ecosystem CO2 exchange (NEE; Reco - GPP), and terrestrial methane (CH4 ) emissions for the Arctic-boreal zone using a satellite data-driven process-model for northern ecosystems (TCFM-Arctic), calibrated and evaluated using measurements from >60 tower eddy covariance (EC) sites. We used TCFM-Arctic to obtain daily 1-km2 flux estimates and annual carbon budgets for the pan-Arctic-boreal region. Across the domain, the model indicated an overall average NEE sink of -850 Tg CO2 -C year-1 . Eurasian boreal zones, especially those in Siberia, contributed to a majority of the net sink. In contrast, the tundra biome was relatively carbon neutral (ranging from small sink to source). Regional CH4 emissions from tundra and boreal wetlands (not accounting for aquatic CH4 ) were estimated at 35 Tg CH4 -C year-1 . Accounting for additional emissions from open water aquatic bodies and from fire, using available estimates from the literature, reduced the total regional NEE sink by 21% and shifted many far northern tundra landscapes, and some boreal forests, to a net carbon source. This assessment, based on in situ observations and models, improves our understanding of the high-latitude carbon status and also indicates a continued need for integrated site-to-regional assessments to monitor the vulnerability of these ecosystems to climate change.

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Pan‐Arctic soil moisture control on tundra carbon sequestration and plant productivity
Donatella Zona, Peter M. Lafleur, Koen Hufkens, Beniamino Gioli, Barbara Bailey, George Burba, E. S. Euskirchen, Jennifer D. Watts, Kyle A. Arndt, Mary Farina, John S. Kimball, Martin Heimann, Mathias Göckede, Martijn Pallandt, Torben R. Christensen, Mikhail Mastepanov, Efrèn López‐Blanco, A. J. Dolman, R. Commane, Charles E. Miller, Josh Hashemi, Lars Kutzbach, David Holl, Julia Boike, Christian Wille, Torsten Sachs, Aram Kalhori, Elyn Humphreys, Oliver Sonnentag, Gesa Meyer, Gabriel Hould Gosselin, Philip Marsh, Walter C. Oechel, Donatella Zona, Peter M. Lafleur, Koen Hufkens, Beniamino Gioli, Barbara Bailey, George Burba, E. S. Euskirchen, Jennifer D. Watts, Kyle A. Arndt, Mary Farina, John S. Kimball, Martin Heimann, Mathias Göckede, Martijn Pallandt, Torben R. Christensen, Mikhail Mastepanov, Efrèn López‐Blanco, A. J. Dolman, R. Commane, Charles E. Miller, Josh Hashemi, Lars Kutzbach, David Holl, Julia Boike, Christian Wille, Torsten Sachs, Aram Kalhori, Elyn Humphreys, Oliver Sonnentag, Gesa Meyer, Gabriel Hould Gosselin, Philip Marsh, Walter C. Oechel
Global Change Biology, Volume 29, Issue 5

Long-term atmospheric CO2 concentration records have suggested a reduction in the positive effect of warming on high-latitude carbon uptake since the 1990s. A variety of mechanisms have been proposed to explain the reduced net carbon sink of northern ecosystems with increased air temperature, including water stress on vegetation and increased respiration over recent decades. However, the lack of consistent long-term carbon flux and in situ soil moisture data has severely limited our ability to identify the mechanisms responsible for the recent reduced carbon sink strength. In this study, we used a record of nearly 100 site-years of eddy covariance data from 11 continuous permafrost tundra sites distributed across the circumpolar Arctic to test the temperature (expressed as growing degree days, GDD) responses of gross primary production (GPP), net ecosystem exchange (NEE), and ecosystem respiration (ER) at different periods of the summer (early, peak, and late summer) including dominant tundra vegetation classes (graminoids and mosses, and shrubs). We further tested GPP, NEE, and ER relationships with soil moisture and vapor pressure deficit to identify potential moisture limitations on plant productivity and net carbon exchange. Our results show a decrease in GPP with rising GDD during the peak summer (July) for both vegetation classes, and a significant relationship between the peak summer GPP and soil moisture after statistically controlling for GDD in a partial correlation analysis. These results suggest that tundra ecosystems might not benefit from increased temperature as much as suggested by several terrestrial biosphere models, if decreased soil moisture limits the peak summer plant productivity, reducing the ability of these ecosystems to sequester carbon during the summer.

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A boreal forest model benchmarking dataset for North America: a case study with the Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC)
Bo Qu, Alexandre Roy, Joe R. Melton, T. Andrew Black, B. D. Amiro, E. S. Euskirchen, Masahito Ueyama, Hideki Kobayashi, Christopher Schulze, Gabriel Hould Gosselin, Alex J. Cannon, Matteo Detto, Oliver Sonnentag
Environmental Research Letters, Volume 18, Issue 8

Abstract Climate change is rapidly altering composition, structure, and functioning of the boreal biome, across North America often broadly categorized into ecoregions. The resulting complex changes in different ecoregions present a challenge for efforts to accurately simulate carbon dioxide (CO 2 ) and energy exchanges between boreal forests and the atmosphere with terrestrial ecosystem models (TEMs). Eddy covariance measurements provide valuable information for evaluating the performance of TEMs and guiding their development. Here, we compiled a boreal forest model benchmarking dataset for North America by harmonizing eddy covariance and supporting measurements from eight black spruce ( Picea mariana )-dominated, mature forest stands. The eight forest stands, located in six boreal ecoregions of North America, differ in stand characteristics, disturbance history, climate, permafrost conditions and soil properties. By compiling various data streams, the benchmarking dataset comprises data to parameterize, force, and evaluate TEMs. Specifically, it includes half-hourly, gap-filled meteorological forcing data, ancillary data essential for model parameterization, and half-hourly, gap-filled or partitioned component flux data on CO 2 (net ecosystem production, gross primary production [GPP], and ecosystem respiration [ER]) and energy (latent [LE] and sensible heat [H]) and their daily aggregates screened based on half-hourly gap-filling quality criteria. We present a case study with the Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC) to: (1) demonstrate the utility of our dataset to benchmark TEMs and (2) provide guidance for model development and refinement. Model skill was evaluated using several statistical metrics and further examined through the flux responses to their environmental controls. Our results suggest that CLASSIC tended to overestimate GPP and ER among all stands. Model performance regarding the energy fluxes (i.e., LE and H) varied greatly among the stands and exhibited a moderate correlation with latitude. We identified strong relationships between simulated fluxes and their environmental controls except for H, thus highlighting current strengths and limitations of CLASSIC.

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Upscaling Wetland Methane Emissions From the FLUXNET‐CH4 Eddy Covariance Network (UpCH4 v1.0): Model Development, Network Assessment, and Budget Comparison
Gavin McNicol, Etienne Fluet‐Chouinard, Zutao Ouyang, Sara Knox, Zhen Zhang, Tuula Aalto, Sheel Bansal, Kuang‐Yu Chang, Min Chen, Kyle Delwiche, Sarah Féron, Mathias Goeckede, Jinxun Liu, Avni Malhotra, Joe R. Melton, W. J. Riley, Rodrigo Vargas, Kunxiaojia Yuan, Qing Ying, Qing Zhu, Pavel Alekseychik, Mika Aurela, David P. Billesbach, David I. Campbell, Jiquan Chen, Housen Chu, Ankur R. Desai, E. S. Euskirchen, Jordan P. Goodrich, Timothy J. Griffis, Manuel Helbig, Takashi Hirano, Hiroki Iwata, Gerald Jurasinski, John S. King, Franziska Koebsch, Randall K. Kolka, Ken W. Krauss, Annalea Lohila, Ivan Mammarella, Mats E Nilson, Asko Noormets, Walter C. Oechel, Matthias Peichl, Torsten Sachs, Ayaka Sakabe, Christopher Schulze, Oliver Sonnentag, Ryan C. Sullivan, Eeva‐Stiina Tuittila, Masahito Ueyama, Timo Vesala, Eric J. Ward, Christian Wille, Guan Xhuan Wong, Donatella Zona, L. Windham‐Myers, Benjamin Poulter, Robert B. Jackson
AGU Advances, Volume 4, Issue 5

Abstract Wetlands are responsible for 20%–31% of global methane (CH 4 ) emissions and account for a large source of uncertainty in the global CH 4 budget. Data‐driven upscaling of CH 4 fluxes from eddy covariance measurements can provide new and independent bottom‐up estimates of wetland CH 4 emissions. Here, we develop a six‐predictor random forest upscaling model (UpCH4), trained on 119 site‐years of eddy covariance CH 4 flux data from 43 freshwater wetland sites in the FLUXNET‐CH4 Community Product. Network patterns in site‐level annual means and mean seasonal cycles of CH 4 fluxes were reproduced accurately in tundra, boreal, and temperate regions (Nash‐Sutcliffe Efficiency ∼0.52–0.63 and 0.53). UpCH4 estimated annual global wetland CH 4 emissions of 146 ± 43 TgCH 4 y −1 for 2001–2018 which agrees closely with current bottom‐up land surface models (102–181 TgCH 4 y −1 ) and overlaps with top‐down atmospheric inversion models (155–200 TgCH 4 y −1 ). However, UpCH4 diverged from both types of models in the spatial pattern and seasonal dynamics of tropical wetland emissions. We conclude that upscaling of eddy covariance CH 4 fluxes has the potential to produce realistic extra‐tropical wetland CH 4 emissions estimates which will improve with more flux data. To reduce uncertainty in upscaled estimates, researchers could prioritize new wetland flux sites along humid‐to‐arid tropical climate gradients, from major rainforest basins (Congo, Amazon, and SE Asia), into monsoon (Bangladesh and India) and savannah regions (African Sahel) and be paired with improved knowledge of wetland extent seasonal dynamics in these regions. The monthly wetland methane products gridded at 0.25° from UpCH4 are available via ORNL DAAC ( https://doi.org/10.3334/ORNLDAAC/2253 ).

2022

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Warming response of peatland CO2 sink is sensitive to seasonality in warming trends
Manuel Helbig, Tatjana Živković, Pavel Alekseychik, Mika Aurela, Tarek S. El‐Madany, E. S. Euskirchen, Lawrence B. Flanagan, Timothy J. Griffis, Paul J. Hanson, J. Hattakka, Carole Helfter, Takashi Hirano, Elyn Humphreys, Gerard Kiely, Randall K. Kolka, Tuomas Laurila, Paul Leahy, Annalea Lohila, Ivan Mammarella, Mats B. Nilsson, A. V. Panov, Frans‐Jan W. Parmentier, Matthias Peichl, Janne Rinne, D. Tyler Roman, Oliver Sonnentag, Eeva‐Stiina Tuittila, Masahito Ueyama, Timo Vesala, Patrik Vestin, Simon Weldon, Per Weslien, Sönke Zaehle
Nature Climate Change, Volume 12, Issue 8

Peatlands have acted as net CO2 sinks over millennia, exerting a global climate cooling effect. Rapid warming at northern latitudes, where peatlands are abundant, can disturb their CO2 sink function. Here we show that sensitivity of peatland net CO2 exchange to warming changes in sign and magnitude across seasons, resulting in complex net CO2 sink responses. We use multiannual net CO2 exchange observations from 20 northern peatlands to show that warmer early summers are linked to increased net CO2 uptake, while warmer late summers lead to decreased net CO2 uptake. Thus, net CO2 sinks of peatlands in regions experiencing early summer warming, such as central Siberia, are more likely to persist under warmer climate conditions than are those in other regions. Our results will be useful to improve the design of future warming experiments and to better interpret large-scale trends in peatland net CO2 uptake over the coming few decades.

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Earlier snowmelt may lead to late season declines in plant productivity and carbon sequestration in Arctic tundra ecosystems
Donatella Zona, Peter M. Lafleur, Koen Hufkens, Barbara Bailey, Beniamino Gioli, George Burba, Jordan P. Goodrich, A. K. Liljedahl, E. S. Euskirchen, Jennifer D. Watts, Mary Farina, John S. Kimball, Martin Heimann, Mathias Göckede, Martijn Pallandt, Torben R. Christensen, Mikhail Mastepanov, Efrèn López‐Blanco, M. Jackowicz-Korczyński, A. J. Dolman, Luca Belelli Marchesini, R. Commane, Steven C. Wofsy, Charles E. Miller, David A. Lipson, Josh Hashemi, Kyle A. Arndt, Lars Kutzbach, David Holl, Julia Boike, Christian Wille, Torsten Sachs, Aram Kalhori, Xia Song, Xiaofeng Xu, Elyn Humphreys, Charles D. Koven, Oliver Sonnentag, Gesa Meyer, Gabriel Hould Gosselin, Philip Marsh, Walter C. Oechel
Scientific Reports, Volume 12, Issue 1

Arctic warming is affecting snow cover and soil hydrology, with consequences for carbon sequestration in tundra ecosystems. The scarcity of observations in the Arctic has limited our understanding of the impact of covarying environmental drivers on the carbon balance of tundra ecosystems. In this study, we address some of these uncertainties through a novel record of 119 site-years of summer data from eddy covariance towers representing dominant tundra vegetation types located on continuous permafrost in the Arctic. Here we found that earlier snowmelt was associated with more tundra net CO2 sequestration and higher gross primary productivity (GPP) only in June and July, but with lower net carbon sequestration and lower GPP in August. Although higher evapotranspiration (ET) can result in soil drying with the progression of the summer, we did not find significantly lower soil moisture with earlier snowmelt, nor evidence that water stress affected GPP in the late growing season. Our results suggest that the expected increased CO2 sequestration arising from Arctic warming and the associated increase in growing season length may not materialize if tundra ecosystems are not able to continue sequestering CO2 later in the season.

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The ABCflux database: Arctic–boreal CO2 flux observations and ancillary information aggregated to monthly time steps across terrestrial ecosystems
Anna‐Maria Virkkala, Susan M. Natali, Brendan M. Rogers, Jennifer D. Watts, K. E. Savage, Sara June Connon, Marguerite Mauritz, Edward A. G. Schuur, D. L. Peter, Christina Minions, Julia Nojeim, R. Commane, Craig A. Emmerton, Mathias Goeckede, Manuel Helbig, David Holl, Hiroki Iwata, Hideki Kobayashi, Pasi Kolari, Efrèn López‐Blanco, Maija E. Marushchak, Mikhail Mastepanov, Lutz Merbold, Frans‐Jan W. Parmentier, Matthias Peichl, Torsten Sachs, Oliver Sonnentag, Masahito Ueyama, Carolina Voigt, Mika Aurela, Julia Boike, Gerardo Celis, Namyi Chae, Torben R. Christensen, M. Syndonia Bret‐Harte, Sigrid Dengel, A. J. Dolman, Colin W. Edgar, Bo Elberling, E. S. Euskirchen, Achim Grelle, Juha Hatakka, Elyn Humphreys, Järvi Järveoja, Ayumi Kotani, Lars Kutzbach, Tuomas Laurila, Annalea Lohila, Ivan Mammarella, Yojiro Matsuura, Gesa Meyer, Mats B. Nilsson, Steven F. Oberbauer, Sang‐Jong Park, Roman Petrov, Anatoly Prokushkin, Christopher Schulze, Vincent L. St. Louis, Eeva‐Stiina Tuittila, Juha‐Pekka Tuovinen, W. L. Quinton, Andrej Varlagin, Donatella Zona, Viacheslav I. Zyryanov
Earth System Science Data, Volume 14, Issue 1

Abstract. Past efforts to synthesize and quantify the magnitude and change in carbon dioxide (CO2) fluxes in terrestrial ecosystems across the rapidly warming Arctic–boreal zone (ABZ) have provided valuable information but were limited in their geographical and temporal coverage. Furthermore, these efforts have been based on data aggregated over varying time periods, often with only minimal site ancillary data, thus limiting their potential to be used in large-scale carbon budget assessments. To bridge these gaps, we developed a standardized monthly database of Arctic–boreal CO2 fluxes (ABCflux) that aggregates in situ measurements of terrestrial net ecosystem CO2 exchange and its derived partitioned component fluxes: gross primary productivity and ecosystem respiration. The data span from 1989 to 2020 with over 70 supporting variables that describe key site conditions (e.g., vegetation and disturbance type), micrometeorological and environmental measurements (e.g., air and soil temperatures), and flux measurement techniques. Here, we describe these variables, the spatial and temporal distribution of observations, the main strengths and limitations of the database, and the potential research opportunities it enables. In total, ABCflux includes 244 sites and 6309 monthly observations; 136 sites and 2217 monthly observations represent tundra, and 108 sites and 4092 observations represent the boreal biome. The database includes fluxes estimated with chamber (19 % of the monthly observations), snow diffusion (3 %) and eddy covariance (78 %) techniques. The largest number of observations were collected during the climatological summer (June–August; 32 %), and fewer observations were available for autumn (September–October; 25 %), winter (December–February; 18 %), and spring (March–May; 25 %). ABCflux can be used in a wide array of empirical, remote sensing and modeling studies to improve understanding of the regional and temporal variability in CO2 fluxes and to better estimate the terrestrial ABZ CO2 budget. ABCflux is openly and freely available online (Virkkala et al., 2021b, https://doi.org/10.3334/ORNLDAAC/1934).

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Causality guided machine learning model on wetland CH4 emissions across global wetlands
Kunxiaojia Yuan, Qing Zhu, Fa Li, W. J. Riley, Margaret Torn, Housen Chu, Gavin McNicol, Min Chen, Sara Knox, Kyle Delwiche, Huayi Wu, Dennis Baldocchi, Hongxu Ma, Ankur R. Desai, Jiquan Chen, Torsten Sachs, Masahito Ueyama, Oliver Sonnentag, Manuel Helbig, Eeva‐Stiina Tuittila, Gerald Jurasinski, Franziska Koebsch, David I. Campbell, Hans Peter Schmid, Annalea Lohila, Mathias Goeckede, Mats B. Nilsson, Thomas Friborg, Joachim Jansen, Donatella Zona, E. S. Euskirchen, Eric J. Ward, Gil Bohrer, Zhenong Jin, Licheng Liu, Hiroki Iwata, Jordan P. Goodrich, Robert B. Jackson
Agricultural and Forest Meteorology, Volume 324

Wetland CH4 emissions are among the most uncertain components of the global CH4 budget. The complex nature of wetland CH4 processes makes it challenging to identify causal relationships for improving our understanding and predictability of CH4 emissions. In this study, we used the flux measurements of CH4 from eddy covariance towers (30 sites from 4 wetlands types: bog, fen, marsh, and wet tundra) to construct a causality-constrained machine learning (ML) framework to explain the regulative factors and to capture CH4 emissions at sub-seasonal scale. We found that soil temperature is the dominant factor for CH4 emissions in all studied wetland types. Ecosystem respiration (CO2) and gross primary productivity exert controls at bog, fen, and marsh sites with lagged responses of days to weeks. Integrating these asynchronous environmental and biological causal relationships in predictive models significantly improved model performance. More importantly, modeled CH4 emissions differed by up to a factor of 4 under a +1°C warming scenario when causality constraints were considered. These results highlight the significant role of causality in modeling wetland CH4 emissions especially under future warming conditions, while traditional data-driven ML models may reproduce observations for the wrong reasons. Our proposed causality-guided model could benefit predictive modeling, large-scale upscaling, data gap-filling, and surrogate modeling of wetland CH4 emissions within earth system land models.

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Vegetation type is an important predictor of the arctic summer land surface energy budget
Jacqueline Oehri, Gabriela Schaepman‐Strub, Jin‐Soo Kim, Raleigh Grysko, Heather Kropp, Inge Grünberg, Vitalii Zemlianskii, Oliver Sonnentag, E. S. Euskirchen, Merin Reji Chacko, Giovanni Muscari, Peter D. Blanken, Joshua Dean, Alcide di Sarra, R. J. Harding, Ireneusz Sobota, Lars Kutzbach, Elena Plekhanova, Aku Riihelä, Julia Boike, Nathaniel B. Miller, Jason Beringer, Efrèn López‐Blanco, Paul C. Stoy, Ryan C. Sullivan, Marek Kejna, Frans‐Jan W. Parmentier, John A. Gamon, Mikhail Mastepanov, Christian Wille, M. Jackowicz-Korczyński, Dirk Nikolaus Karger, W. L. Quinton, Jaakko Putkonen, Dirk van As, Torben R. Christensen, Maria Z. Hakuba, Robert S. Stone, Stefan Metzger, Baptiste Vandecrux, Gerald V. Frost, Martin Wild, Birger Ulf Hansen, Daniela Meloni, Florent Dominé, Mariska te Beest, Torsten Sachs, Aram Kalhori, Adrian V. Rocha, Scott Williamson, Sara Morris, A. L. Atchley, Richard Essery, Benjamin R. K. Runkle, David Holl, Laura Riihimaki, Hiroki Iwata, Edward A. G. Schuur, Christopher J. Cox, Andrey A. Grachev, J. P. McFadden, Robert S. Fausto, Mathias Göckede, Masahito Ueyama, Norbert Pirk, Gijs de Boer, M. Syndonia Bret‐Harte, Matti Leppäranta, Konrad Steffen, Thomas Friborg, Atsumu Ohmura, Colin W. Edgar, Johan Olofsson, Scott Chambers
Nature Communications, Volume 13, Issue 1

Abstract Despite the importance of high-latitude surface energy budgets (SEBs) for land-climate interactions in the rapidly changing Arctic, uncertainties in their prediction persist. Here, we harmonize SEB observations across a network of vegetated and glaciated sites at circumpolar scale (1994–2021). Our variance-partitioning analysis identifies vegetation type as an important predictor for SEB-components during Arctic summer (June-August), compared to other SEB-drivers including climate, latitude and permafrost characteristics. Differences among vegetation types can be of similar magnitude as between vegetation and glacier surfaces and are especially high for summer sensible and latent heat fluxes. The timing of SEB-flux summer-regimes (when daily mean values exceed 0 Wm −2 ) relative to snow-free and -onset dates varies substantially depending on vegetation type, implying vegetation controls on snow-cover and SEB-flux seasonality. Our results indicate complex shifts in surface energy fluxes with land-cover transitions and a lengthening summer season, and highlight the potential for improving future Earth system models via a refined representation of Arctic vegetation types.

2021

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The Boreal-Arctic Wetland and Lake Dataset (BAWLD)
David Olefeldt, Mikael Hovemyr, McKenzie A. Kuhn, David Bastviken, T. J. Bohn, John Connolly, P. M. Crill, E. S. Euskirchen, Sarah A. Finkelstein, Hélène Genet, Guido Grosse, Lorna I. Harris, Liam Heffernan, Manuel Helbig, Gustaf Hugelius, Ryan Hutchins, Sari Juutinen, Mark J. Lara, Avni Malhotra, Kristen Manies, A. David McGuire, Susan M. Natali, Jonathan A. O’Donnell, Frans‐Jan W. Parmentier, Aleksi Räsänen, Christina Schädel, Oliver Sonnentag, Maria Strack, Suzanne E. Tank, Claire C. Treat, R. K. Varner, Tarmo Virtanen, Rebecca K. Warren, Jennifer D. Watts, David Olefeldt, Mikael Hovemyr, McKenzie A. Kuhn, David Bastviken, T. J. Bohn, John Connolly, P. M. Crill, E. S. Euskirchen, Sarah A. Finkelstein, Hélène Genet, Guido Grosse, Lorna I. Harris, Liam Heffernan, Manuel Helbig, Gustaf Hugelius, Ryan Hutchins, Sari Juutinen, Mark J. Lara, Avni Malhotra, Kristen Manies, A. David McGuire, Susan M. Natali, Jonathan A. O’Donnell, Frans‐Jan W. Parmentier, Aleksi Räsänen, Christina Schädel, Oliver Sonnentag, Maria Strack, Suzanne E. Tank, Claire C. Treat, R. K. Varner, Tarmo Virtanen, Rebecca K. Warren, Jennifer D. Watts

Abstract. Methane emissions from boreal and arctic wetlands, lakes, and rivers are expected to increase in response to warming and associated permafrost thaw. However, the lack of appropriate land cover datasets for scaling field-measured methane emissions to circumpolar scales has contributed to a large uncertainty for our understanding of present-day and future methane emissions. Here we present the Boreal-Arctic Wetland and Lake Dataset (BAWLD), a land cover dataset based on an expert assessment, extrapolated using random forest modelling from available spatial datasets of climate, topography, soils, permafrost conditions, vegetation, wetlands, and surface water extents and dynamics. In BAWLD, we estimate the fractional coverage of five wetland, seven lake, and three river classes within 0.5 × 0.5° grid cells that cover the northern boreal and tundra biomes (17 % of the global land surface). Land cover classes were defined using criteria that ensured distinct methane emissions among classes, as indicated by a co-developed comprehensive dataset of methane flux observations. In BAWLD, wetlands occupied 3.2 × 106 km2 (14 % of domain) with a 95 % confidence interval between 2.8 and 3.8 × 106 km2. Bog, fen, and permafrost bog were the most abundant wetland classes, covering ~28 % each of the total wetland area, while the highest methane emitting marsh and tundra wetland classes occupied 5 and 12 %, respectively. Lakes, defined to include all lentic open-water ecosystems regardless of size, covered 1.4 × 106 km2 (6 % of domain). Low methane-emitting large lakes (> 10 km2) and glacial lakes jointly represented 78 % of the total lake area, while high-emitting peatland and yedoma lakes covered 18 and 4 %, respectively. Small (< 0.1 km2) glacial, peatland, and yedoma lakes combined covered 17 % of the total lake area, but contributed disproportionally to the overall spatial uncertainty of lake area with a 95 % confidence interval between 0.15 and 0.38 × 106 km2. Rivers and streams were estimated to cover 0.12 × 106 km2 (0.5 % of domain) of which 8 % was associated with high-methane emitting headwaters that drain organic-rich landscapes. Distinct combinations of spatially co-occurring wetland and lake classes were identified across the BAWLD domain, allowing for the mapping of “wetscapes” that will have characteristic methane emission magnitudes and sensitivities to climate change at regional scales. With BAWLD, we provide a dataset which avoids double-accounting of wetland, lake and river extents, and which includes confidence intervals for each land cover class. As such, BAWLD will be suitable for many hydrological and biogeochemical modelling and upscaling efforts for the northern Boreal and Arctic region, in particular those aimed at improving assessments of current and future methane emissions. Data is freely available at https://doi.org/10.18739/A2C824F9X (Olefeldt et al., 2021).

DOI bib abs
FLUXNET-CH4: a global, multi-ecosystem dataset and analysis of methane seasonality from freshwater wetlands
Kyle Delwiche, Sara Knox, Avni Malhotra, Etienne Fluet‐Chouinard, Gavin McNicol, Sarah Féron, Zutao Ouyang, Dario Papale, Carlo Trotta, Eleonora Canfora, You-Wei Cheah, Danielle Christianson, Ma. Carmelita Alberto, Pavel Alekseychik, Mika Aurela, Dennis Baldocchi, Sheel Bansal, David P. Billesbach, Gil Bohrer, Rosvel Bracho, Nina Buchmann, David I. Campbell, Gerardo Celis, Jiquan Chen, Weinan Chen, Housen Chu, Higo J. Dalmagro, Sigrid Dengel, Ankur R. Desai, Matteo Detto, A. J. Dolman, Elke Eichelmann, E. S. Euskirchen, D. Famulari, Kathrin Fuchs, Mathias Goeckede, Sébastien Gogo, Mangaliso J. Gondwe, Jordan P. Goodrich, Pia Gottschalk, Scott L. Graham, Martin Heimann, Manuel Helbig, Carole Helfter, Kyle S. Hemes, Takashi Hirano, David Y. Hollinger, Lukas Hörtnagl, Hiroki Iwata, Adrien Jacotot, Gerald Jurasinski, Minseok Kang, Kuno Kasak, John S. King, Janina Klatt, Franziska Koebsch, Ken W. Krauss, Derrick Y.F. Lai, Annalea Lohila, Ivan Mammarella, Luca Belelli Marchesini, Giovanni Manca, Jaclyn Hatala Matthes, Trofim C. Maximov, Lutz Merbold, Bhaskar Mitra, Timothy H. Morin, Eiko Nemitz, Mats B. Nilsson, Shuli Niu, Walter C. Oechel, Patricia Y. Oikawa, Keisuke Ono, Matthias Peichl, Olli Peltola, Michele L. Reba, Andrew D. Richardson, W. J. Riley, Benjamin R. K. Runkle, Youngryel Ryu, Torsten Sachs, Ayaka Sakabe, Camilo Rey‐Sánchez, Edward A. G. Schuur, Karina V. R. Schäfer, Oliver Sonnentag, Jed P. Sparks, Ellen Stuart‐Haëntjens, Cove Sturtevant, Ryan C. Sullivan, Daphne Szutu, Jonathan E. Thom, Margaret Torn, Eeva‐Stiina Tuittila, Jessica Turner, Masahito Ueyama, Alex Valach, Rodrigo Vargas, Andrej Varlagin, Alma Vázquez‐Lule, Joseph Verfaillie, Timo Vesala, George L. Vourlitis, Eric J. Ward, Christian Wille, Georg Wohlfahrt, Guan Xhuan Wong, Zhen Zhang, Donatella Zona, L. Windham‐Myers, Benjamin Poulter, Robert B. Jackson, Kyle Delwiche, Sara Knox, Avni Malhotra, Etienne Fluet‐Chouinard, Gavin McNicol, Sarah Féron, Zutao Ouyang, Dario Papale, Carlo Trotta, Eleonora Canfora, You-Wei Cheah, Danielle Christianson, Ma. Carmelita Alberto, Pavel Alekseychik, Mika Aurela, Dennis Baldocchi, Sheel Bansal, David P. Billesbach, Gil Bohrer, Rosvel Bracho, Nina Buchmann, David I. Campbell, Gerardo Celis, Jiquan Chen, Weinan Chen, Housen Chu, Higo J. Dalmagro, Sigrid Dengel, Ankur R. Desai, Matteo Detto, A. J. Dolman, Elke Eichelmann, E. S. Euskirchen, D. Famulari, Kathrin Fuchs, Mathias Goeckede, Sébastien Gogo, Mangaliso J. Gondwe, Jordan P. Goodrich, Pia Gottschalk, Scott L. Graham, Martin Heimann, Manuel Helbig, Carole Helfter, Kyle S. Hemes, Takashi Hirano, David Y. Hollinger, Lukas Hörtnagl, Hiroki Iwata, Adrien Jacotot, Gerald Jurasinski, Minseok Kang, Kuno Kasak, John S. King, Janina Klatt, Franziska Koebsch, Ken W. Krauss, Derrick Y.F. Lai, Annalea Lohila, Ivan Mammarella, Luca Belelli Marchesini, Giovanni Manca, Jaclyn Hatala Matthes, Trofim C. Maximov, Lutz Merbold, Bhaskar Mitra, Timothy H. Morin, Eiko Nemitz, Mats B. Nilsson, Shuli Niu, Walter C. Oechel, Patricia Y. Oikawa, Keisuke Ono, Matthias Peichl, Olli Peltola, Michele L. Reba, Andrew D. Richardson, W. J. Riley, Benjamin R. K. Runkle, Youngryel Ryu, Torsten Sachs, Ayaka Sakabe, Camilo Rey‐Sánchez, Edward A. G. Schuur, Karina V. R. Schäfer, Oliver Sonnentag, Jed P. Sparks, Ellen Stuart‐Haëntjens, Cove Sturtevant, Ryan C. Sullivan, Daphne Szutu, Jonathan E. Thom, Margaret Torn, Eeva‐Stiina Tuittila, Jessica Turner, Masahito Ueyama, Alex Valach, Rodrigo Vargas, Andrej Varlagin, Alma Vázquez‐Lule, Joseph Verfaillie, Timo Vesala, George L. Vourlitis, Eric J. Ward, Christian Wille, Georg Wohlfahrt, Guan Xhuan Wong, Zhen Zhang, Donatella Zona, L. Windham‐Myers, Benjamin Poulter, Robert B. Jackson
Earth System Science Data, Volume 13, Issue 7

Abstract. Methane (CH4) emissions from natural landscapes constitute roughly half of global CH4 contributions to the atmosphere, yet large uncertainties remain in the absolute magnitude and the seasonality of emission quantities and drivers. Eddy covariance (EC) measurements of CH4 flux are ideal for constraining ecosystem-scale CH4 emissions due to quasi-continuous and high-temporal-resolution CH4 flux measurements, coincident carbon dioxide, water, and energy flux measurements, lack of ecosystem disturbance, and increased availability of datasets over the last decade. Here, we (1) describe the newly published dataset, FLUXNET-CH4 Version 1.0, the first open-source global dataset of CH4 EC measurements (available at https://fluxnet.org/data/fluxnet-ch4-community-product/, last access: 7 April 2021). FLUXNET-CH4 includes half-hourly and daily gap-filled and non-gap-filled aggregated CH4 fluxes and meteorological data from 79 sites globally: 42 freshwater wetlands, 6 brackish and saline wetlands, 7 formerly drained ecosystems, 7 rice paddy sites, 2 lakes, and 15 uplands. Then, we (2) evaluate FLUXNET-CH4 representativeness for freshwater wetland coverage globally because the majority of sites in FLUXNET-CH4 Version 1.0 are freshwater wetlands which are a substantial source of total atmospheric CH4 emissions; and (3) we provide the first global estimates of the seasonal variability and seasonality predictors of freshwater wetland CH4 fluxes. Our representativeness analysis suggests that the freshwater wetland sites in the dataset cover global wetland bioclimatic attributes (encompassing energy, moisture, and vegetation-related parameters) in arctic, boreal, and temperate regions but only sparsely cover humid tropical regions. Seasonality metrics of wetland CH4 emissions vary considerably across latitudinal bands. In freshwater wetlands (except those between 20∘ S to 20∘ N) the spring onset of elevated CH4 emissions starts 3 d earlier, and the CH4 emission season lasts 4 d longer, for each degree Celsius increase in mean annual air temperature. On average, the spring onset of increasing CH4 emissions lags behind soil warming by 1 month, with very few sites experiencing increased CH4 emissions prior to the onset of soil warming. In contrast, roughly half of these sites experience the spring onset of rising CH4 emissions prior to the spring increase in gross primary productivity (GPP). The timing of peak summer CH4 emissions does not correlate with the timing for either peak summer temperature or peak GPP. Our results provide seasonality parameters for CH4 modeling and highlight seasonality metrics that cannot be predicted by temperature or GPP (i.e., seasonality of CH4 peak). FLUXNET-CH4 is a powerful new resource for diagnosing and understanding the role of terrestrial ecosystems and climate drivers in the global CH4 cycle, and future additions of sites in tropical ecosystems and site years of data collection will provide added value to this database. All seasonality parameters are available at https://doi.org/10.5281/zenodo.4672601 (Delwiche et al., 2021). Additionally, raw FLUXNET-CH4 data used to extract seasonality parameters can be downloaded from https://fluxnet.org/data/fluxnet-ch4-community-product/ (last access: 7 April 2021), and a complete list of the 79 individual site data DOIs is provided in Table 2 of this paper.

DOI bib abs
Substantial hysteresis in emergent temperature sensitivity of global wetland CH4 emissions
Kuang‐Yu Chang, W. J. Riley, Sara Knox, Robert B. Jackson, Gavin McNicol, Benjamin Poulter, Mika Aurela, Dennis Baldocchi, Sheel Bansal, Gil Bohrer, David I. Campbell, Alessandro Cescatti, Housen Chu, Kyle Delwiche, Ankur R. Desai, E. S. Euskirchen, Thomas Friborg, Mathias Goeckede, Manuel Helbig, Kyle S. Hemes, Takashi Hirano, Hiroki Iwata, Minseok Kang, Trevor F. Keenan, Ken W. Krauss, Annalea Lohila, Ivan Mammarella, Bhaskar Mitra, Akira Miyata, Mats B. Nilsson, Asko Noormets, Walter C. Oechel, Dario Papale, Matthias Peichl, Michele L. Reba, Janne Rinne, Benjamin R. K. Runkle, Youngryel Ryu, Torsten Sachs, Karina V. R. Schäfer, Hans Peter Schmid, Narasinha Shurpali, Oliver Sonnentag, Angela C. I. Tang, Margaret Torn, Carlo Trotta, Eeva‐Stiina Tuittila, Masahito Ueyama, Rodrigo Vargas, Timo Vesala, L. Windham‐Myers, Zhen Zhang, Donatella Zona, Kuang‐Yu Chang, W. J. Riley, Sara Knox, Robert B. Jackson, Gavin McNicol, Benjamin Poulter, Mika Aurela, Dennis Baldocchi, Sheel Bansal, Gil Bohrer, David I. Campbell, Alessandro Cescatti, Housen Chu, Kyle Delwiche, Ankur R. Desai, E. S. Euskirchen, Thomas Friborg, Mathias Goeckede, Manuel Helbig, Kyle S. Hemes, Takashi Hirano, Hiroki Iwata, Minseok Kang, Trevor F. Keenan, Ken W. Krauss, Annalea Lohila, Ivan Mammarella, Bhaskar Mitra, Akira Miyata, Mats B. Nilsson, Asko Noormets, Walter C. Oechel, Dario Papale, Matthias Peichl, Michele L. Reba, Janne Rinne, Benjamin R. K. Runkle, Youngryel Ryu, Torsten Sachs, Karina V. R. Schäfer, Hans Peter Schmid, Narasinha Shurpali, Oliver Sonnentag, Angela C. I. Tang, Margaret Torn, Carlo Trotta, Eeva‐Stiina Tuittila, Masahito Ueyama, Rodrigo Vargas, Timo Vesala, L. Windham‐Myers, Zhen Zhang, Donatella Zona
Nature Communications, Volume 12, Issue 1

Abstract Wetland methane (CH 4 ) emissions ( $${F}_{{{CH}}_{4}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mrow> <mml:mi>F</mml:mi> </mml:mrow> <mml:mrow> <mml:msub> <mml:mrow> <mml:mi>C</mml:mi> <mml:mi>H</mml:mi> </mml:mrow> <mml:mrow> <mml:mn>4</mml:mn> </mml:mrow> </mml:msub> </mml:mrow> </mml:msub> </mml:math> ) are important in global carbon budgets and climate change assessments. Currently, $${F}_{{{CH}}_{4}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mrow> <mml:mi>F</mml:mi> </mml:mrow> <mml:mrow> <mml:msub> <mml:mrow> <mml:mi>C</mml:mi> <mml:mi>H</mml:mi> </mml:mrow> <mml:mrow> <mml:mn>4</mml:mn> </mml:mrow> </mml:msub> </mml:mrow> </mml:msub> </mml:math> projections rely on prescribed static temperature sensitivity that varies among biogeochemical models. Meta-analyses have proposed a consistent $${F}_{{{CH}}_{4}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mrow> <mml:mi>F</mml:mi> </mml:mrow> <mml:mrow> <mml:msub> <mml:mrow> <mml:mi>C</mml:mi> <mml:mi>H</mml:mi> </mml:mrow> <mml:mrow> <mml:mn>4</mml:mn> </mml:mrow> </mml:msub> </mml:mrow> </mml:msub> </mml:math> temperature dependence across spatial scales for use in models; however, site-level studies demonstrate that $${F}_{{{CH}}_{4}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mrow> <mml:mi>F</mml:mi> </mml:mrow> <mml:mrow> <mml:msub> <mml:mrow> <mml:mi>C</mml:mi> <mml:mi>H</mml:mi> </mml:mrow> <mml:mrow> <mml:mn>4</mml:mn> </mml:mrow> </mml:msub> </mml:mrow> </mml:msub> </mml:math> are often controlled by factors beyond temperature. Here, we evaluate the relationship between $${F}_{{{CH}}_{4}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mrow> <mml:mi>F</mml:mi> </mml:mrow> <mml:mrow> <mml:msub> <mml:mrow> <mml:mi>C</mml:mi> <mml:mi>H</mml:mi> </mml:mrow> <mml:mrow> <mml:mn>4</mml:mn> </mml:mrow> </mml:msub> </mml:mrow> </mml:msub> </mml:math> and temperature using observations from the FLUXNET-CH 4 database. Measurements collected across the globe show substantial seasonal hysteresis between $${F}_{{{CH}}_{4}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mrow> <mml:mi>F</mml:mi> </mml:mrow> <mml:mrow> <mml:msub> <mml:mrow> <mml:mi>C</mml:mi> <mml:mi>H</mml:mi> </mml:mrow> <mml:mrow> <mml:mn>4</mml:mn> </mml:mrow> </mml:msub> </mml:mrow> </mml:msub> </mml:math> and temperature, suggesting larger $${F}_{{{CH}}_{4}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mrow> <mml:mi>F</mml:mi> </mml:mrow> <mml:mrow> <mml:msub> <mml:mrow> <mml:mi>C</mml:mi> <mml:mi>H</mml:mi> </mml:mrow> <mml:mrow> <mml:mn>4</mml:mn> </mml:mrow> </mml:msub> </mml:mrow> </mml:msub> </mml:math> sensitivity to temperature later in the frost-free season (about 77% of site-years). Results derived from a machine-learning model and several regression models highlight the importance of representing the large spatial and temporal variability within site-years and ecosystem types. Mechanistic advancements in biogeochemical model parameterization and detailed measurements in factors modulating CH 4 production are thus needed to improve global CH 4 budget assessments.

DOI bib abs
Gap-filling eddy covariance methane fluxes: Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands
Jeremy Irvin, Sharon Zhou, Gavin McNicol, Fred Lu, Vincent Liu, Etienne Fluet‐Chouinard, Zutao Ouyang, Sara Knox, Antje Lucas-Moffat, Carlo Trotta, Dario Papale, Domenico Vitale, Ivan Mammarella, Pavel Alekseychik, Mika Aurela, Anand Avati, Dennis Baldocchi, Sheel Bansal, Gil Bohrer, David I. Campbell, Jiquan Chen, Housen Chu, Higo J. Dalmagro, Kyle Delwiche, Ankur R. Desai, E. S. Euskirchen, Sarah Féron, Mathias Goeckede, Martin Heimann, Manuel Helbig, Carole Helfter, Kyle S. Hemes, Takashi Hirano, Hiroki Iwata, Gerald Jurasinski, Aram Kalhori, Andrew Kondrich, Derrick Y.F. Lai, Annalea Lohila, Avni Malhotra, Lutz Merbold, Bhaskar Mitra, Andrew Y. Ng, Mats B. Nilsson, Asko Noormets, Matthias Peichl, Camilo Rey‐Sánchez, Andrew D. Richardson, Benjamin R. K. Runkle, Karina VR Schäfer, Oliver Sonnentag, Ellen Stuart‐Haëntjens, Cove Sturtevant, Masahito Ueyama, Alex Valach, Rodrigo Vargas, George L. Vourlitis, Eric J. Ward, Guan Xhuan Wong, Donatella Zona, Ma. Carmelita Alberto, David P. Billesbach, Gerardo Celis, A. J. Dolman, Thomas Friborg, Kathrin Fuchs, Sébastien Gogo, Mangaliso J. Gondwe, Jordan P. Goodrich, Pia Gottschalk, Lukas Hörtnagl, Adrien Jacotot, Franziska Koebsch, Kuno Kasak, Regine Maier, Timothy H. Morin, Eiko Nemitz, Walter C. Oechel, Patricia Y. Oikawa, Keisuke Ono, Torsten Sachs, Ayaka Sakabe, Edward A. G. Schuur, Robert Shortt, Ryan C. Sullivan, Daphne Szutu, Eeva‐Stiina Tuittila, Andrej Varlagin, Joeseph G Verfaillie, Christian Wille, L. Windham‐Myers, Benjamin Poulter, Robert B. Jackson, Jeremy Irvin, Sharon Zhou, Gavin McNicol, Fred Lu, Vincent Liu, Etienne Fluet‐Chouinard, Zutao Ouyang, Sara Knox, Antje Lucas-Moffat, Carlo Trotta, Dario Papale, Domenico Vitale, Ivan Mammarella, Pavel Alekseychik, Mika Aurela, Anand Avati, Dennis Baldocchi, Sheel Bansal, Gil Bohrer, David I. Campbell, Jiquan Chen, Housen Chu, Higo J. Dalmagro, Kyle Delwiche, Ankur R. Desai, E. S. Euskirchen, Sarah Féron, Mathias Goeckede, Martin Heimann, Manuel Helbig, Carole Helfter, Kyle S. Hemes, Takashi Hirano, Hiroki Iwata, Gerald Jurasinski, Aram Kalhori, Andrew Kondrich, Derrick Y.F. Lai, Annalea Lohila, Avni Malhotra, Lutz Merbold, Bhaskar Mitra, Andrew Y. Ng, Mats B. Nilsson, Asko Noormets, Matthias Peichl, Camilo Rey‐Sánchez, Andrew D. Richardson, Benjamin R. K. Runkle, Karina VR Schäfer, Oliver Sonnentag, Ellen Stuart‐Haëntjens, Cove Sturtevant, Masahito Ueyama, Alex Valach, Rodrigo Vargas, George L. Vourlitis, Eric J. Ward, Guan Xhuan Wong, Donatella Zona, Ma. Carmelita Alberto, David P. Billesbach, Gerardo Celis, A. J. Dolman, Thomas Friborg, Kathrin Fuchs, Sébastien Gogo, Mangaliso J. Gondwe, Jordan P. Goodrich, Pia Gottschalk, Lukas Hörtnagl, Adrien Jacotot, Franziska Koebsch, Kuno Kasak, Regine Maier, Timothy H. Morin, Eiko Nemitz, Walter C. Oechel, Patricia Y. Oikawa, Keisuke Ono, Torsten Sachs, Ayaka Sakabe, Edward A. G. Schuur, Robert Shortt, Ryan C. Sullivan, Daphne Szutu, Eeva‐Stiina Tuittila, Andrej Varlagin, Joeseph G Verfaillie, Christian Wille, L. Windham‐Myers, Benjamin Poulter, Robert B. Jackson
Agricultural and Forest Meteorology, Volume 308-309

• We evaluate methane flux gap-filling methods across 17 boreal-to-tropical wetlands • New methods for generating realistic artificial gaps and uncertainties are proposed • Decision tree algorithms perform slightly better than neural networks on average • Soil temperature and generic seasonality are the most important predictors • Open-source code is released for gap-filling steps and uncertainty evaluation Time series of wetland methane fluxes measured by eddy covariance require gap-filling to estimate daily, seasonal, and annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for wetland methane fluxes, with regards both to the best model algorithms and predictors. This study synthesizes results of different gap-filling methods systematically applied at 17 wetland sites spanning boreal to tropical regions and including all major wetland classes and two rice paddies. Procedures are proposed for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting half-hourly methane fluxes and annual emissions with realistic uncertainty estimates. Performance is compared between a conventional method (marginal distribution sampling) and four machine learning algorithms. The conventional method achieved similar median performance as the machine learning models but was worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on wetland soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. The python code for model development, evaluation, and uncertainty estimation is publicly available. This study outlines a modular and robust machine learning workflow and makes recommendations for, and evaluates an improved baseline of, methane gap-filling models that can be implemented in multi-site syntheses or standardized products from regional and global flux networks (e.g., FLUXNET).

DOI bib abs
Identifying dominant environmental predictors of freshwater wetland methane fluxes across diurnal to seasonal time scales
Sara Knox, Sheel Bansal, Gavin McNicol, Karina V. R. Schäfer, Cove Sturtevant, Masahito Ueyama, Alex Valach, Dennis Baldocchi, Kyle Delwiche, Ankur R. Desai, E. S. Euskirchen, Jinxun Liu, Annalea Lohila, Avni Malhotra, Lulie Melling, W. J. Riley, Benjamin R. K. Runkle, Jessica Turner, Rodrigo Vargas, Qing Zhu, Tuula Alto, Etienne Fluet‐Chouinard, Mathias Goeckede, Joe R. Melton, Oliver Sonnentag, Timo Vesala, Eric J. Ward, Zhen Zhang, Sarah Féron, Zutao Ouyang, Pavel Alekseychik, Mika Aurela, Gil Bohrer, David I. Campbell, Jiquan Chen, Housen Chu, Higo J. Dalmagro, Jordan P. Goodrich, Pia Gottschalk, Takashi Hirano, Hiroki Iwata, Gerald Jurasinski, Minseok Kang, Franziska Koebsch, Ivan Mammarella, Mats B. Nilsson, Keisuke Ono, Matthias Peichl, Olli Peltola, Youngryel Ryu, Torsten Sachs, Ayaka Sakabe, Jed P. Sparks, Eeva‐Stiina Tuittila, George L. Vourlitis, Guan Xhuan Wong, L. Windham‐Myers, Benjamin Poulter, Robert B. Jackson, Sara Knox, Sheel Bansal, Gavin McNicol, Karina V. R. Schäfer, Cove Sturtevant, Masahito Ueyama, Alex Valach, Dennis Baldocchi, Kyle Delwiche, Ankur R. Desai, E. S. Euskirchen, Jinxun Liu, Annalea Lohila, Avni Malhotra, Lulie Melling, W. J. Riley, Benjamin R. K. Runkle, Jessica Turner, Rodrigo Vargas, Qing Zhu, Tuula Alto, Etienne Fluet‐Chouinard, Mathias Goeckede, Joe R. Melton, Oliver Sonnentag, Timo Vesala, Eric J. Ward, Zhen Zhang, Sarah Féron, Zutao Ouyang, Pavel Alekseychik, Mika Aurela, Gil Bohrer, David I. Campbell, Jiquan Chen, Housen Chu, Higo J. Dalmagro, Jordan P. Goodrich, Pia Gottschalk, Takashi Hirano, Hiroki Iwata, Gerald Jurasinski, Minseok Kang, Franziska Koebsch, Ivan Mammarella, Mats B. Nilsson, Keisuke Ono, Matthias Peichl, Olli Peltola, Youngryel Ryu, Torsten Sachs, Ayaka Sakabe, Jed P. Sparks, Eeva‐Stiina Tuittila, George L. Vourlitis, Guan Xhuan Wong, L. Windham‐Myers, Benjamin Poulter, Robert B. Jackson
Global Change Biology, Volume 27, Issue 15

While wetlands are the largest natural source of methane (CH4) to the atmosphere, they represent a large source of uncertainty in the global CH4 budget due to the complex biogeochemical controls on CH4 dynamics. Here we present, to our knowledge, the first multi-site synthesis of how predictors of CH4 fluxes (FCH4) in freshwater wetlands vary across wetland types at diel, multiday (synoptic), and seasonal time scales. We used several statistical approaches (correlation analysis, generalized additive modeling, mutual information, and random forests) in a wavelet-based multi-resolution framework to assess the importance of environmental predictors, nonlinearities and lags on FCH4 across 23 eddy covariance sites. Seasonally, soil and air temperature were dominant predictors of FCH4 at sites with smaller seasonal variation in water table depth (WTD). In contrast, WTD was the dominant predictor for wetlands with smaller variations in temperature (e.g., seasonal tropical/subtropical wetlands). Changes in seasonal FCH4 lagged fluctuations in WTD by ~17 ± 11 days, and lagged air and soil temperature by median values of 8 ± 16 and 5 ± 15 days, respectively. Temperature and WTD were also dominant predictors at the multiday scale. Atmospheric pressure (PA) was another important multiday scale predictor for peat-dominated sites, with drops in PA coinciding with synchronous releases of CH4. At the diel scale, synchronous relationships with latent heat flux and vapor pressure deficit suggest that physical processes controlling evaporation and boundary layer mixing exert similar controls on CH4 volatilization, and suggest the influence of pressurized ventilation in aerenchymatous vegetation. In addition, 1- to 4-h lagged relationships with ecosystem photosynthesis indicate recent carbon substrates, such as root exudates, may also control FCH4. By addressing issues of scale, asynchrony, and nonlinearity, this work improves understanding of the predictors and timing of wetland FCH4 that can inform future studies and models, and help constrain wetland CH4 emissions.

DOI bib abs
Statistical upscaling of ecosystem CO 2 fluxes across the terrestrial tundra and boreal domain: Regional patterns and uncertainties
Anna‐Maria Virkkala, Juha Aalto, Brendan M. Rogers, Torbern Tagesson, Claire C. Treat, Susan M. Natali, Jennifer D. Watts, Stefano Potter, Aleksi Lehtonen, Marguerite Mauritz, Edward A. G. Schuur, John Kochendorfer, Donatella Zona, Walter C. Oechel, Hideki Kobayashi, Elyn Humphreys, Mathias Goeckede, Hiroki Iwata, Peter M. Lafleur, E. S. Euskirchen, Stef Bokhorst, Maija E. Marushchak, Pertti J. Martikainen, Bo Elberling, Carolina Voigt, Christina Biasi, Oliver Sonnentag, Frans‐Jan W. Parmentier, Masahito Ueyama, Gerardo Celis, Vincent L. St. Louis, Craig A. Emmerton, Matthias Peichl, Jinshu Chi, Järvi Järveoja, Mats B. Nilsson, Steven F. Oberbauer, Margaret Torn, Sang‐Jong Park, A. J. Dolman, Ivan Mammarella, Namyi Chae, Rafael Poyatos, Efrèn López‐Blanco, Torben R. Christensen, Min Jung Kwon, Torsten Sachs, David Holl, Miska Luoto, Anna‐Maria Virkkala, Juha Aalto, Brendan M. Rogers, Torbern Tagesson, Claire C. Treat, Susan M. Natali, Jennifer D. Watts, Stefano Potter, Aleksi Lehtonen, Marguerite Mauritz, Edward A. G. Schuur, John Kochendorfer, Donatella Zona, Walter C. Oechel, Hideki Kobayashi, Elyn Humphreys, Mathias Goeckede, Hiroki Iwata, Peter M. Lafleur, E. S. Euskirchen, Stef Bokhorst, Maija E. Marushchak, Pertti J. Martikainen, Bo Elberling, Carolina Voigt, Christina Biasi, Oliver Sonnentag, Frans‐Jan W. Parmentier, Masahito Ueyama, Gerardo Celis, Vincent L. St. Louis, Craig A. Emmerton, Matthias Peichl, Jinshu Chi, Järvi Järveoja, Mats B. Nilsson, Steven F. Oberbauer, Margaret Torn, Sang‐Jong Park, A. J. Dolman, Ivan Mammarella, Namyi Chae, Rafael Poyatos, Efrèn López‐Blanco, Torben R. Christensen, Min Jung Kwon, Torsten Sachs, David Holl, Miska Luoto
Global Change Biology, Volume 27, Issue 17

The regional variability in tundra and boreal carbon dioxide (CO2) fluxes can be high, complicating efforts to quantify sink-source patterns across the entire region. Statistical models are increasingly used to predict (i.e., upscale) CO2 fluxes across large spatial domains, but the reliability of different modeling techniques, each with different specifications and assumptions, has not been assessed in detail. Here, we compile eddy covariance and chamber measurements of annual and growing season CO2 fluxes of gross primary productivity (GPP), ecosystem respiration (ER), and net ecosystem exchange (NEE) during 1990–2015 from 148 terrestrial high-latitude (i.e., tundra and boreal) sites to analyze the spatial patterns and drivers of CO2 fluxes and test the accuracy and uncertainty of different statistical models. CO2 fluxes were upscaled at relatively high spatial resolution (1 km2) across the high-latitude region using five commonly used statistical models and their ensemble, that is, the median of all five models, using climatic, vegetation, and soil predictors. We found the performance of machine learning and ensemble predictions to outperform traditional regression methods. We also found the predictive performance of NEE-focused models to be low, relative to models predicting GPP and ER. Our data compilation and ensemble predictions showed that CO2 sink strength was larger in the boreal biome (observed and predicted average annual NEE −46 and −29 g C m−2 yr−1, respectively) compared to tundra (average annual NEE +10 and −2 g C m−2 yr−1). This pattern was associated with large spatial variability, reflecting local heterogeneity in soil organic carbon stocks, climate, and vegetation productivity. The terrestrial ecosystem CO2 budget, estimated using the annual NEE ensemble prediction, suggests the high-latitude region was on average an annual CO2 sink during 1990–2015, although uncertainty remains high.

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Soil respiration strongly offsets carbon uptake in Alaska and Northwest Canada
Jennifer D. Watts, Susan M. Natali, Christina Minions, D. A. Risk, Kyle A. Arndt, Donatella Zona, E. S. Euskirchen, Adrian V. Rocha, Oliver Sonnentag, Manuel Helbig, Aram Kalhori, Walter C. Oechel, Hiroki Ikawa, Masahito Ueyama, Rikie Suzuki, Hideki Kobayashi, Gerardo Celis, Edward A. G. Schuur, Elyn Humphreys, Yongwon Kim, Bang‐Yong Lee, S. J. Goetz, Nima Madani, Luke D. Schiferl, R. Commane, John S. Kimball, Zhihua Liu, Margaret Torn, Stefano Potter, Jonathan Wang, M. Torre Jorgenson, Jingfeng Xiao, Xing Li, Colin W. Edgar, Jennifer D. Watts, Susan M. Natali, Christina Minions, D. A. Risk, Kyle A. Arndt, Donatella Zona, E. S. Euskirchen, Adrian V. Rocha, Oliver Sonnentag, Manuel Helbig, Aram Kalhori, Walter C. Oechel, Hiroki Ikawa, Masahito Ueyama, Rikie Suzuki, Hideki Kobayashi, Gerardo Celis, Edward A. G. Schuur, Elyn Humphreys, Yongwon Kim, Bang‐Yong Lee, S. J. Goetz, Nima Madani, Luke D. Schiferl, R. Commane, John S. Kimball, Zhihua Liu, Margaret Torn, Stefano Potter, Jonathan Wang, M. Torre Jorgenson, Jingfeng Xiao, Xing Li, Colin W. Edgar
Environmental Research Letters, Volume 16, Issue 8

Abstract Soil respiration (i.e. from soils and roots) provides one of the largest global fluxes of carbon dioxide (CO 2 ) to the atmosphere and is likely to increase with warming, yet the magnitude of soil respiration from rapidly thawing Arctic-boreal regions is not well understood. To address this knowledge gap, we first compiled a new CO 2 flux database for permafrost-affected tundra and boreal ecosystems in Alaska and Northwest Canada. We then used the CO 2 database, multi-sensor satellite imagery, and random forest models to assess the regional magnitude of soil respiration. The flux database includes a new Soil Respiration Station network of chamber-based fluxes, and fluxes from eddy covariance towers. Our site-level data, spanning September 2016 to August 2017, revealed that the largest soil respiration emissions occurred during the summer (June–August) and that summer fluxes were higher in boreal sites (1.87 ± 0.67 g CO 2 –C m −2 d −1 ) relative to tundra (0.94 ± 0.4 g CO 2 –C m −2 d −1 ). We also observed considerable emissions (boreal: 0.24 ± 0.2 g CO 2 –C m −2 d −1 ; tundra: 0.18 ± 0.16 g CO 2 –C m −2 d −1 ) from soils during the winter (November–March) despite frozen surface conditions. Our model estimates indicated an annual region-wide loss from soil respiration of 591 ± 120 Tg CO 2 –C during the 2016–2017 period. Summer months contributed to 58% of the regional soil respiration, winter months contributed to 15%, and the shoulder months contributed to 27%. In total, soil respiration offset 54% of annual gross primary productivity (GPP) across the study domain. We also found that in tundra environments, transitional tundra/boreal ecotones, and in landscapes recently affected by fire, soil respiration often exceeded GPP, resulting in a net annual source of CO 2 to the atmosphere. As this region continues to warm, soil respiration may increasingly offset GPP, further amplifying global climate change.

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Global transpiration data from sap flow measurements: the SAPFLUXNET database
Rafael Poyatos, Víctor Granda, Víctor Flo, Mark A. Adams, Balázs Adorján, David Aguadé, Marcos Pereira Marinho Aidar, Scott T. Allen, M. S. Alvarado-Barrientos, Kristina J. Anderson‐Teixeira, L. M. T. Aparecido, M. Altaf Arain, Ismael Aranda, Heidi Asbjornsen, Robert Baxter, Eric Beamesderfer, Z. Carter Berry, Daniel Berveiller, Bethany Blakely, Johnny Boggs, Gil Bohrer, Paul V. Bolstad, Damien Bonal, Rosvel Bracho, Patricia Brito, Jason Brodeur, Fernando Casanoves, Jérôme Chave, Hui Chen, César Cisneros Vaca, Kenneth L. Clark, Edoardo Cremonese, Hongzhong Dang, Jorge S. David, Teresa S. David, Nicolas Delpierre, Ankur R. Desai, C. Frédéric, Michal Dohnal, Jean‐Christophe Domec, Sebinasi Dzikiti, Colin W. Edgar, Rebekka Eichstaedt, Tarek S. El‐Madany, J.A. Elbers, Cleiton B. Eller, E. S. Euskirchen, B. E. Ewers, Patrick Fonti, Alicia Forner, David I. Forrester, Helber C. Freitas, Marta Galvagno, Omar García-Tejera, Chandra Prasad Ghimire, Teresa E. Gimeno, J. P. Grace, André Granier, Anne Griebel, Yan Guangyu, M.B. Gush, Paul J. Hanson, Niles J. Hasselquist, Ingo Heinrich, Virginia Hernández‐Santana, Valentine Herrmann, Teemu Hölttä, F. Holwerda, J. E. Irvine, Supat Isarangkool Na Ayutthaya, P. G. Jarvis, Hubert Jochheim, Carlos Alfredo Joly, Julia Kaplick, Hyun Seok Kim, Leif Klemedtsson, Heather Kropp, Fredrik Lagergren, Patrick N.J. Lane, Petra Lang, Andrei Lapenas, Víctor Lechuga, Minsu Lee, Christoph Leuschner, Jean‐Marc Limousin, Juan Carlos Linares, Maj‐Lena Linderson, Anders Lindroth, Pilar Llorens, Álvaro López‐Bernal, M. M. Loranty, Dietmar Lüttschwager, Cate Macinnis‐Ng, Isabelle Maréchaux, Timothy A. Martin, Ashley M. Matheny, Nate G. McDowell, Sean M. McMahon, Patrick Meir, Ilona Mészáros, Mirco Migliavacca, Patrick J. Mitchell, Meelis Mölder, Leonardo Montagnani, Georgianne W. Moore, Ryogo Nakada, Furong Niu, Rachael H. Nolan, Richard J. Norby, Kimberly A. Novick, Walter Oberhuber, Nikolaus Obojes, A. Christopher Oishi, Rafael S. Oliveira, Ram Oren, Jean‐Marc Ourcival, Teemu Paljakka, Óscar Pérez‐Priego, Pablo Luís Peri, Richard L. Peters, Sebastian Pfautsch, William T. Pockman, Yakir Preisler, Katherine G. Rascher, George R. Robinson, Humberto Ribeiro da Rocha, Alain Rocheteau, Alexander Röll, Bruno H. P. Rosado, Lucy Rowland, Alexey V. Rubtsov, Santiago Sabaté, Yann Salmon, Roberto L. Salomón, Elisenda Sánchez‐Costa, Karina V. R. Schäfer, Bernhard Schuldt, Alexandr Shashkin, Clément Stahl, Marko Stojanović, Juan Carlos Suárez, Ge Sun, Justyna Szatniewska, Fyodor Tatarinov, Miroslav Tesař, Frank M. Thomas, Pantana Tor‐ngern, Josef Urban, Fernando Valladares, Christiaan van der Tol, Ilja van Meerveld, Andrej Varlagin, Holm Voigt, J. M. Warren, Christiane Werner, Willy Werner, Gerhard Wieser, Lisa Wingate, Stan Wullschleger, K. Yi, Roman Zweifel, Kathy Steppe, Maurizio Mencuccini, Jordi Martínez‐Vilalta, Rafael Poyatos, Víctor Granda, Víctor Flo, Mark A. Adams, Balázs Adorján, David Aguadé, Marcos Pereira Marinho Aidar, Scott T. Allen, M. S. Alvarado-Barrientos, Kristina J. Anderson‐Teixeira, L. M. T. Aparecido, M. Altaf Arain, Ismael Aranda, Heidi Asbjornsen, Robert Baxter, Eric Beamesderfer, Z. Carter Berry, Daniel Berveiller, Bethany Blakely, Johnny Boggs, Gil Bohrer, Paul V. Bolstad, Damien Bonal, Rosvel Bracho, Patricia Brito, Jason Brodeur, Fernando Casanoves, Jérôme Chave, Hui Chen, César Cisneros Vaca, Kenneth L. Clark, Edoardo Cremonese, Hongzhong Dang, Jorge S. David, Teresa S. David, Nicolas Delpierre, Ankur R. Desai, C. Frédéric, Michal Dohnal, Jean‐Christophe Domec, Sebinasi Dzikiti, Colin W. Edgar, Rebekka Eichstaedt, Tarek S. El‐Madany, J.A. Elbers, Cleiton B. Eller, E. S. Euskirchen, B. E. Ewers, Patrick Fonti, Alicia Forner, David I. Forrester, Helber C. Freitas, Marta Galvagno, Omar García-Tejera, Chandra Prasad Ghimire, Teresa E. Gimeno, J. P. Grace, André Granier, Anne Griebel, Yan Guangyu, M.B. Gush, Paul J. Hanson, Niles J. Hasselquist, Ingo Heinrich, Virginia Hernández‐Santana, Valentine Herrmann, Teemu Hölttä, F. Holwerda, J. E. Irvine, Supat Isarangkool Na Ayutthaya, P. G. Jarvis, Hubert Jochheim, Carlos Alfredo Joly, Julia Kaplick, Hyun Seok Kim, Leif Klemedtsson, Heather Kropp, Fredrik Lagergren, Patrick N.J. Lane, Petra Lang, Andrei Lapenas, Víctor Lechuga, Minsu Lee, Christoph Leuschner, Jean‐Marc Limousin, Juan Carlos Linares, Maj‐Lena Linderson, Anders Lindroth, Pilar Llorens, Álvaro López‐Bernal, M. M. Loranty, Dietmar Lüttschwager, Cate Macinnis‐Ng, Isabelle Maréchaux, Timothy A. Martin, Ashley M. Matheny, Nate G. McDowell, Sean M. McMahon, Patrick Meir, Ilona Mészáros, Mirco Migliavacca, Patrick J. Mitchell, Meelis Mölder, Leonardo Montagnani, Georgianne W. Moore, Ryogo Nakada, Furong Niu, Rachael H. Nolan, Richard J. Norby, Kimberly A. Novick, Walter Oberhuber, Nikolaus Obojes, A. Christopher Oishi, Rafael S. Oliveira, Ram Oren, Jean‐Marc Ourcival, Teemu Paljakka, Óscar Pérez‐Priego, Pablo Luís Peri, Richard L. Peters, Sebastian Pfautsch, William T. Pockman, Yakir Preisler, Katherine G. Rascher, George R. Robinson, Humberto Ribeiro da Rocha, Alain Rocheteau, Alexander Röll, Bruno H. P. Rosado, Lucy Rowland, Alexey V. Rubtsov, Santiago Sabaté, Yann Salmon, Roberto L. Salomón, Elisenda Sánchez‐Costa, Karina V. R. Schäfer, Bernhard Schuldt, Alexandr Shashkin, Clément Stahl, Marko Stojanović, Juan Carlos Suárez, Ge Sun, Justyna Szatniewska, Fyodor Tatarinov, Miroslav Tesař, Frank M. Thomas, Pantana Tor‐ngern, Josef Urban, Fernando Valladares, Christiaan van der Tol, Ilja van Meerveld, Andrej Varlagin, Holm Voigt, J. M. Warren, Christiane Werner, Willy Werner, Gerhard Wieser, Lisa Wingate, Stan Wullschleger, K. Yi, Roman Zweifel, Kathy Steppe, Maurizio Mencuccini, Jordi Martínez‐Vilalta
Earth System Science Data, Volume 13, Issue 6

Abstract. Plant transpiration links physiological responses of vegetation to water supply and demand with hydrological, energy, and carbon budgets at the land–atmosphere interface. However, despite being the main land evaporative flux at the global scale, transpiration and its response to environmental drivers are currently not well constrained by observations. Here we introduce the first global compilation of whole-plant transpiration data from sap flow measurements (SAPFLUXNET, https://sapfluxnet.creaf.cat/, last access: 8 June 2021). We harmonized and quality-controlled individual datasets supplied by contributors worldwide in a semi-automatic data workflow implemented in the R programming language. Datasets include sub-daily time series of sap flow and hydrometeorological drivers for one or more growing seasons, as well as metadata on the stand characteristics, plant attributes, and technical details of the measurements. SAPFLUXNET contains 202 globally distributed datasets with sap flow time series for 2714 plants, mostly trees, of 174 species. SAPFLUXNET has a broad bioclimatic coverage, with woodland/shrubland and temperate forest biomes especially well represented (80 % of the datasets). The measurements cover a wide variety of stand structural characteristics and plant sizes. The datasets encompass the period between 1995 and 2018, with 50 % of the datasets being at least 3 years long. Accompanying radiation and vapour pressure deficit data are available for most of the datasets, while on-site soil water content is available for 56 % of the datasets. Many datasets contain data for species that make up 90 % or more of the total stand basal area, allowing the estimation of stand transpiration in diverse ecological settings. SAPFLUXNET adds to existing plant trait datasets, ecosystem flux networks, and remote sensing products to help increase our understanding of plant water use, plant responses to drought, and ecohydrological processes. SAPFLUXNET version 0.1.5 is freely available from the Zenodo repository (https://doi.org/10.5281/zenodo.3971689; Poyatos et al., 2020a). The “sapfluxnetr” R package – designed to access, visualize, and process SAPFLUXNET data – is available from CRAN.

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The Boreal–Arctic Wetland and Lake Dataset (BAWLD)
David Olefeldt, Mikael Hovemyr, McKenzie A. Kuhn, David Bastviken, T. J. Bohn, John Connolly, P. M. Crill, E. S. Euskirchen, Sarah A. Finkelstein, Hélène Genet, Guido Grosse, Lorna I. Harris, Liam Heffernan, Manuel Helbig, Gustaf Hugelius, Ryan Hutchins, Sari Juutinen, Mark J. Lara, Avni Malhotra, Kristen Manies, A. David McGuire, Susan M. Natali, Jonathan A. O’Donnell, Frans‐Jan W. Parmentier, Aleksi Räsänen, Christina Schädel, Oliver Sonnentag, Maria Strack, Suzanne E. Tank, Claire C. Treat, R. K. Varner, Tarmo Virtanen, Rebecca K. Warren, Jennifer D. Watts
Earth System Science Data, Volume 13, Issue 11

Abstract. Methane emissions from boreal and arctic wetlands, lakes, and rivers are expected to increase in response to warming and associated permafrost thaw. However, the lack of appropriate land cover datasets for scaling field-measured methane emissions to circumpolar scales has contributed to a large uncertainty for our understanding of present-day and future methane emissions. Here we present the Boreal–Arctic Wetland and Lake Dataset (BAWLD), a land cover dataset based on an expert assessment, extrapolated using random forest modelling from available spatial datasets of climate, topography, soils, permafrost conditions, vegetation, wetlands, and surface water extents and dynamics. In BAWLD, we estimate the fractional coverage of five wetland, seven lake, and three river classes within 0.5 × 0.5∘ grid cells that cover the northern boreal and tundra biomes (17 % of the global land surface). Land cover classes were defined using criteria that ensured distinct methane emissions among classes, as indicated by a co-developed comprehensive dataset of methane flux observations. In BAWLD, wetlands occupied 3.2 × 106 km2 (14 % of domain) with a 95 % confidence interval between 2.8 and 3.8 × 106 km2. Bog, fen, and permafrost bog were the most abundant wetland classes, covering ∼ 28 % each of the total wetland area, while the highest-methane-emitting marsh and tundra wetland classes occupied 5 % and 12 %, respectively. Lakes, defined to include all lentic open-water ecosystems regardless of size, covered 1.4 × 106 km2 (6 % of domain). Low-methane-emitting large lakes (>10 km2) and glacial lakes jointly represented 78 % of the total lake area, while high-emitting peatland and yedoma lakes covered 18 % and 4 %, respectively. Small (<0.1 km2) glacial, peatland, and yedoma lakes combined covered 17 % of the total lake area but contributed disproportionally to the overall spatial uncertainty in lake area with a 95 % confidence interval between 0.15 and 0.38 × 106 km2. Rivers and streams were estimated to cover 0.12 × 106 km2 (0.5 % of domain), of which 8 % was associated with high-methane-emitting headwaters that drain organic-rich landscapes. Distinct combinations of spatially co-occurring wetland and lake classes were identified across the BAWLD domain, allowing for the mapping of “wetscapes” that have characteristic methane emission magnitudes and sensitivities to climate change at regional scales. With BAWLD, we provide a dataset which avoids double-accounting of wetland, lake, and river extents and which includes confidence intervals for each land cover class. As such, BAWLD will be suitable for many hydrological and biogeochemical modelling and upscaling efforts for the northern boreal and arctic region, in particular those aimed at improving assessments of current and future methane emissions. Data are freely available at https://doi.org/10.18739/A2C824F9X (Olefeldt et al., 2021).

2020

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Shallow soils are warmer under trees and tall shrubs across Arctic and Boreal ecosystems
Heather Kropp, M. M. Loranty, Susan M. Natali, Alexander Kholodov, Adrian V. Rocha, Isla H. Myers‐Smith, Benjamin W Abbot, Jakob Abermann, Elena Blanc‐Betes, Daan Blok, Gesche Blume‐Werry, Julia Boike, Amy Breen, Sean M. P. Cahoon, Casper T. Christiansen, Thomas A. Douglas, Howard E. Epstein, Gerald V. Frost, Mathias Goeckede, Toke T. Høye, Steven D. Mamet, Jonathan A. O’Donnell, David Olefeldt, Gareth K. Phoenix, Verity Salmon, A. Britta K. Sannel, Sharon L. Smith, Oliver Sonnentag, Lydia J. S. Vaughn, Mathew Williams, Bo Elberling, Laura Gough, Jan Hjort, Peter M. Lafleur, E. S. Euskirchen, Monique M. P. D. Heijmans, Elyn Humphreys, Hiroki Iwata, Benjamin Jones, M. Torre Jorgenson, Inge Grünberg, Yongwon Kim, James A. Laundre, Marguerite Mauritz, Anders Michelsen, Gabriela Schaepman‐Strub, Ken D. Tape, Masahito Ueyama, Bang‐Yong Lee, Kirsty Langley, Magnus Lund
Environmental Research Letters, Volume 16, Issue 1

Abstract Soils are warming as air temperatures rise across the Arctic and Boreal region concurrent with the expansion of tall-statured shrubs and trees in the tundra. Changes in vegetation structure and function are expected to alter soil thermal regimes, thereby modifying climate feedbacks related to permafrost thaw and carbon cycling. However, current understanding of vegetation impacts on soil temperature is limited to local or regional scales and lacks the generality necessary to predict soil warming and permafrost stability on a pan-Arctic scale. Here we synthesize shallow soil and air temperature observations with broad spatial and temporal coverage collected across 106 sites representing nine different vegetation types in the permafrost region. We showed ecosystems with tall-statured shrubs and trees (>40 cm) have warmer shallow soils than those with short-statured tundra vegetation when normalized to a constant air temperature. In tree and tall shrub vegetation types, cooler temperatures in the warm season do not lead to cooler mean annual soil temperature indicating that ground thermal regimes in the cold-season rather than the warm-season are most critical for predicting soil warming in ecosystems underlain by permafrost. Our results suggest that the expansion of tall shrubs and trees into tundra regions can amplify shallow soil warming, and could increase the potential for increased seasonal thaw depth and increase soil carbon cycling rates and lead to increased carbon dioxide loss and further permafrost thaw.

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Increasing contribution of peatlands to boreal evapotranspiration in a warming climate
Manuel Helbig, J. M. Waddington, Pavel Alekseychik, B. D. Amiro, Mika Aurela, Alan Barr, T. Andrew Black, Peter D. Blanken, Sean K. Carey, Jiquan Chen, Jinshu Chi, Ankur R. Desai, Allison L. Dunn, E. S. Euskirchen, Lawrence B. Flanagan, Inke Forbrich, Thomas Friborg, Achim Grelle, Silvie Harder, Michal Heliasz, Elyn Humphreys, Hiroki Ikawa, Pierre‐Erik Isabelle, Hiroki Iwata, Rachhpal S. Jassal, Mika Korkiakoski, J. Kurbatova, Lars Kutzbach, Anders Lindroth, Mikaell Ottosson Löfvenius, Annalea Lohila, Ivan Mammarella, Philip Marsh, Trofim C. Maximov, Joe R. Melton, Paul Moore, Daniel F. Nadeau, Erin M. Nicholls, Mats B. Nilsson, Takeshi Ohta, Matthias Peichl, Richard M. Petrone, Roman Petrov, Anatoly Prokushkin, W. L. Quinton, David E. Reed, Nigel T. Roulet, Benjamin R. K. Runkle, Oliver Sonnentag, Ian B. Strachan, Pierre Taillardat, Eeva‐Stiina Tuittila, Juha‐Pekka Tuovinen, Jessica Turner, Masahito Ueyama, Andrej Varlagin, Martin Wilmking, Steven C. Wofsy, Vyacheslav Zyrianov
Nature Climate Change, Volume 10, Issue 6

The response of evapotranspiration (ET) to warming is of critical importance to the water and carbon cycle of the boreal biome, a mosaic of land cover types dominated by forests and peatlands. The effect of warming-induced vapour pressure deficit (VPD) increases on boreal ET remains poorly understood because peatlands are not specifically represented as plant functional types in Earth system models. Here we show that peatland ET increases more than forest ET with increasing VPD using observations from 95 eddy covariance tower sites. At high VPD of more than 2 kPa, peatland ET exceeds forest ET by up to 30%. Future (2091–2100) mid-growing season peatland ET is estimated to exceed forest ET by over 20% in about one-third of the boreal biome for RCP4.5 and about two-thirds for RCP8.5. Peatland-specific ET responses to VPD should therefore be included in Earth system models to avoid biases in water and carbon cycle projections.

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The biophysical climate mitigation potential of boreal peatlands during the growing season
Manuel Helbig, J. M. Waddington, Pavel Alekseychik, B. D. Amiro, Mika Aurela, Alan Barr, T. Andrew Black, Sean K. Carey, Jiquan Chen, Jinshu Chi, Ankur R. Desai, Allison L. Dunn, E. S. Euskirchen, Lawrence B. Flanagan, Thomas Friborg, Michelle Garneau, Achim Grelle, Silvie Harder, Michal Heliasz, Elyn Humphreys, Hiroki Ikawa, Pierre‐Erik Isabelle, Hiroki Iwata, Rachhpal S. Jassal, Mika Korkiakoski, J. Kurbatova, Lars Kutzbach, Е. Д. Лапшина, Anders Lindroth, Mikaell Ottosson Löfvenius, Annalea Lohila, Ivan Mammarella, Philip Marsh, Paul Moore, Trofim C. Maximov, Daniel F. Nadeau, Erin M. Nicholls, Mats B. Nilsson, Takeshi Ohta, Matthias Peichl, Richard M. Petrone, Anatoly Prokushkin, W. L. Quinton, Nigel T. Roulet, Benjamin R. K. Runkle, Oliver Sonnentag, Ian B. Strachan, Pierre Taillardat, Eeva‐Stiina Tuittila, Juha‐Pekka Tuovinen, Jessica Turner, Masahito Ueyama, Andrej Varlagin, Timo Vesala, Martin Wilmking, Vyacheslav Zyrianov, Christopher Schulze
Environmental Research Letters, Volume 15, Issue 10

Peatlands and forests cover large areas of the boreal biome and are critical for global climate regulation. They also regulate regional climate through heat and water vapour exchange with the atmosphere. Understanding how land-atmosphere interactions in peatlands differ from forests may therefore be crucial for modelling boreal climate system dynamics and for assessing climate benefits of peatland conservation and restoration. To assess the biophysical impacts of peatlands and forests on peak growing season air temperature and humidity, we analysed surface energy fluxes and albedo from 35 peatlands and 37 evergreen needleleaf forests - the dominant boreal forest type - and simulated air temperature and vapour pressure deficit (VPD) over hypothetical homogeneous peatland and forest landscapes. We ran an evapotranspiration model using land surface parameters derived from energy flux observations and coupled an analytical solution for the surface energy balance to an atmospheric boundary layer (ABL) model. We found that peatlands, compared to forests, are characterized by higher growing season albedo, lower aerodynamic conductance, and higher surface conductance for an equivalent VPD. This combination of peatland surface properties results in a ∼20% decrease in afternoon ABL height, a cooling (from 1.7 to 2.5 °C) in afternoon air temperatures, and a decrease in afternoon VPD (from 0.4 to 0.7 kPa) for peatland landscapes compared to forest landscapes. These biophysical climate impacts of peatlands are most pronounced at lower latitudes (∼45°N) and decrease toward the northern limit of the boreal biome (∼70°N). Thus, boreal peatlands have the potential to mitigate the effect of regional climate warming during the growing season. The biophysical climate mitigation potential of peatlands needs to be accounted for when projecting the future climate of the boreal biome, when assessing the climate benefits of conserving pristine boreal peatlands, and when restoring peatlands that have experienced peatland drainage and mining. © 2020 The Author(s). Published by IOP Publishing Ltd. (Less)

2019

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Increased high‐latitude photosynthetic carbon gain offset by respiration carbon loss during an anomalous warm winter to spring transition
Zhihua Liu, John S. Kimball, N. Parazoo, Ashley P. Ballantyne, Wen J. Wang, Nima Madani, Caleb G. Pan, Jennifer D. Watts, Rolf H. Reichle, Oliver Sonnentag, Philip Marsh, Miriam Hurkuck, Manuel Helbig, W. L. Quinton, Donatella Zona, Masahito Ueyama, Hideki Kobayashi, E. S. Euskirchen
Global Change Biology, Volume 26, Issue 2

Arctic and boreal ecosystems play an important role in the global carbon (C) budget, and whether they act as a future net C sink or source depends on climate and environmental change. Here, we used complementary in situ measurements, model simulations, and satellite observations to investigate the net carbon dioxide (CO2 ) seasonal cycle and its climatic and environmental controls across Alaska and northwestern Canada during the anomalously warm winter to spring conditions of 2015 and 2016 (relative to 2010-2014). In the warm spring, we found that photosynthesis was enhanced more than respiration, leading to greater CO2 uptake. However, photosynthetic enhancement from spring warming was partially offset by greater ecosystem respiration during the preceding anomalously warm winter, resulting in nearly neutral effects on the annual net CO2 balance. Eddy covariance CO2 flux measurements showed that air temperature has a primary influence on net CO2 exchange in winter and spring, while soil moisture has a primary control on net CO2 exchange in the fall. The net CO2 exchange was generally more moisture limited in the boreal region than in the Arctic tundra. Our analysis indicates complex seasonal interactions of underlying C cycle processes in response to changing climate and hydrology that may not manifest in changes in net annual CO2 exchange. Therefore, a better understanding of the seasonal response of C cycle processes may provide important insights for predicting future carbon-climate feedbacks and their consequences on atmospheric CO2 dynamics in the northern high latitudes.

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Large loss of CO2 in winter observed across the northern permafrost region
Susan M. Natali, Jennifer D. Watts, Brendan M. Rogers, Stefano Potter, S. Ludwig, A. K. Selbmann, Patrick F. Sullivan, Benjamin W. Abbott, Kyle A. Arndt, Leah Birch, Mats P. Björkman, A. Anthony Bloom, Gerardo Celis, Torben R. Christensen, Casper T. Christiansen, R. Commane, Elisabeth J. Cooper, P. M. Crill, C. I. Czimczik, S. P. Davydov, Jinyang Du, J. E. Egan, Bo Elberling, E. S. Euskirchen, Thomas Friborg, Hélène Genet, Mathias Göckede, Jordan P. Goodrich, Paul Grogan, Manuel Helbig, Elchin Jafarov, Julie Jastrow, Aram Kalhori, Yongwon Kim, John S. Kimball, Lars Kutzbach, Mark J. Lara, Klaus Steenberg Larsen, Bang-Yong Lee, Zhihua Liu, M. M. Loranty, Magnus Lund, Massimo Lupascu, Nima Madani, Avni Malhotra, Roser Matamala, Jack W. McFarland, A. David McGuire, Anders Michelsen, Christina Minions, Walter C. Oechel, David Olefeldt, Frans‐Jan W. Parmentier, Norbert Pirk, Benjamin Poulter, W. L. Quinton, Fereidoun Rezanezhad, David Risk, Torsten Sachs, Kevin Schaefer, Niels Martin Schmidt, Edward A. G. Schuur, Philipp Semenchuk, Gaius R. Shaver, Oliver Sonnentag, Gregory Starr, Claire C. Treat, Mark P. Waldrop, Yihui Wang, J. M. Welker, Christian Wille, Xiaofeng Xu, Zhen Zhang, Qianlai Zhuang, Donatella Zona
Nature Climate Change, Volume 9, Issue 11

Recent warming in the Arctic, which has been amplified during the winter1-3, greatly enhances microbial decomposition of soil organic matter and subsequent release of carbon dioxide (CO2)4. However, the amount of CO2 released in winter is highly uncertain and has not been well represented by ecosystem models or by empirically-based estimates5,6. Here we synthesize regional in situ observations of CO2 flux from arctic and boreal soils to assess current and future winter carbon losses from the northern permafrost domain. We estimate a contemporary loss of 1662 Tg C yr-1 from the permafrost region during the winter season (October through April). This loss is greater than the average growing season carbon uptake for this region estimated from process models (-1032 Tg C yr-1). Extending model predictions to warmer conditions in 2100 indicates that winter CO2 emissions will increase 17% under a moderate mitigation scenario-Representative Concentration Pathway (RCP) 4.5-and 41% under business-as-usual emissions scenario-RCP 8.5. Our results provide a new baseline for winter CO2 emissions from northern terrestrial regions and indicate that enhanced soil CO2 loss due to winter warming may offset growing season carbon uptake under future climatic conditions.

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Monthly gridded data product of northern wetland methane emissions based on upscaling eddy covariance observations
Olli Peltola, Timo Vesala, Yao Gao, Olle Räty, Pavel Alekseychik, Mika Aurela, Bogdan H. Chojnicki, Ankur R. Desai, A. J. Dolman, E. S. Euskirchen, Thomas Friborg, Mathias Göckede, Manuel Helbig, Elyn Humphreys, Robert B. Jackson, Georg Jocher, Fortunat Joos, Janina Klatt, Sara Knox, Natalia Kowalska, Lars Kutzbach, Sebastian Lienert, Annalea Lohila, Ivan Mammarella, Daniel F. Nadeau, Mats B. Nilsson, Walter C. Oechel, Matthias Peichl, Thomas G. Pypker, W. L. Quinton, Janne Rinne, Torsten Sachs, Mateusz Samson, Hans Peter Schmid, Oliver Sonnentag, Christian Wille, Donatella Zona, Tuula Aalto
Earth System Science Data, Volume 11, Issue 3

Abstract. Natural wetlands constitute the largest and most uncertain source of methane (CH4) to the atmosphere and a large fraction of them are found in the northern latitudes. These emissions are typically estimated using process (“bottom-up”) or inversion (“top-down”) models. However, estimates from these two types of models are not independent of each other since the top-down estimates usually rely on the a priori estimation of these emissions obtained with process models. Hence, independent spatially explicit validation data are needed. Here we utilize a random forest (RF) machine-learning technique to upscale CH4 eddy covariance flux measurements from 25 sites to estimate CH4 wetland emissions from the northern latitudes (north of 45∘ N). Eddy covariance data from 2005 to 2016 are used for model development. The model is then used to predict emissions during 2013 and 2014. The predictive performance of the RF model is evaluated using a leave-one-site-out cross-validation scheme. The performance (Nash–Sutcliffe model efficiency =0.47) is comparable to previous studies upscaling net ecosystem exchange of carbon dioxide and studies comparing process model output against site-level CH4 emission data. The global distribution of wetlands is one major source of uncertainty for upscaling CH4. Thus, three wetland distribution maps are utilized in the upscaling. Depending on the wetland distribution map, the annual emissions for the northern wetlands yield 32 (22.3–41.2, 95 % confidence interval calculated from a RF model ensemble), 31 (21.4–39.9) or 38 (25.9–49.5) Tg(CH4) yr−1. To further evaluate the uncertainties of the upscaled CH4 flux data products we also compared them against output from two process models (LPX-Bern and WetCHARTs), and methodological issues related to CH4 flux upscaling are discussed. The monthly upscaled CH4 flux data products are available at https://doi.org/10.5281/zenodo.2560163 (Peltola et al., 2019).

2018

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Validation of the SMAP freeze/thaw product using categorical triple collocation
Haobo Lyu, Kaighin A. McColl, Xinlu Li, Chris Derksen, Aaron Berg, T. A. Black, E. S. Euskirchen, M. M. Loranty, Jouni Pulliainen, Kimmo Rautiainen, Tracy Rowlandson, Alexandre Roy, A. Royer, Alexandre Langlois, Jilmarie Stephens, Hui Lü, Dara Entekhabi
Remote Sensing of Environment, Volume 205

Abstract The landscape freeze/thaw (FT) state plays an important role in local, regional and global weather and climate, but is difficult to monitor. The Soil Moisture Active Passive (SMAP) satellite mission provides hemispheric estimates of landscape FT state at a spatial resolution of approximately 36 2 km 2 . Previous validation studies of SMAP and other satellite FT products have compared satellite retrievals with point estimates obtained from in-situ measurements of air and/or soil temperature. Differences between the two are attributed to errors in the satellite retrieval. However, significant differences can occur between satellite and in-situ estimates solely due to differences in scale between the measurements; these differences can be viewed as ‘representativeness errors’ in the in-situ product, caused by using a point estimate to represent a large-scale spatial average. Most previous validation studies of landscape FT state have neglected representativeness errors entirely, resulting in conservative estimates of satellite retrieval skill. In this study, we use a variant of triple collocation called ‘categorical triple collocation’ – a technique that uses model, satellite and in-situ estimates to obtain relative performance rankings of all three products, without neglecting representativeness errors – to validate the SMAP landscape FT product. Performance rankings are obtained for nine sites at northern latitudes. We also investigate differences between using air or soil temperatures to estimate FT state, and between using morning (6 AM) or evening (6 PM) estimates. Overall, at most sites, the SMAP product or in-situ FT measurement is ranked first, and the model FT product is ranked last (although rankings vary across sites). These results suggest SMAP is adding value to model simulations, providing higher-accuracy estimates of landscape FT states compared to models and, in some cases, even in-situ estimates, when representativeness errors are properly accounted for in the validation analysis.